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Developing and validating multivariable prediction models for predicting the risk of 7-day neonatal readmission
Sangmin Lee1, Dylan E O'Sullivan2, Darren R Brenner1,3
1Department of Community Health Sciences, University of Calgary, Calgary, Canada.
Insights
Predictive models for 7-day neonatal readmission after birth were developed. Current models show suboptimal performance, indicating a need for further refinement to improve infant care and reduce readmissions.
Area of Science:
- Neonatal health
- Predictive modeling
- Public health
Background:
- Neonatal readmissions pose a significant challenge, with approximately 3.5% of Canadian deliveries resulting in potentially preventable readmissions.
- Identifying infants at high risk for readmission is crucial for effective discharge planning and targeted monitoring.
Purpose of the Study:
- To develop and validate predictive models for 7-day neonatal readmission following both vaginal and cesarean births.
- To identify key predictors of neonatal readmission using administrative health data.
Main Methods:
- Utilized perinatal and hospitalization databases for liveborn, term singleton infants without congenital anomalies in Alberta.
- Employed multivariable logistic regression with backward stepwise selection on a split-sample dataset for model development and external validation.
- Evaluated predictors including maternal age, Apgar score, length-of-stay, birthweight, gestational age, parity, residence, and sex.
Main Results:
- Readmission rates were 3.3% for vaginal births and 2.1% for cesarean births in the development dataset.
- Prediction models demonstrated sub-optimal performance, with c-statistics of 0.68 for vaginal births and 0.64 for cesarean births in validation data.
- Infants in the top quintile for predicted risk showed higher observed readmission rates (7.9% vaginal, 4.9% cesarean).
Conclusions:
- Developed and validated prediction models for neonatal readmission using administrative data.
- Current models are sub-optimal for clinical risk assessment and discharge planning.
- Further research incorporating additional data sources may enhance the predictive performance of these models.
Background:
Approximately 3.5% of deliveries in Canada result in potentially preventable neonatal readmission, often times due to preventable morbidities. With complexities in hospital discharge planning, health care providers may benefit in identifying infants at risk of readmission for additional monitoring.
Objectives:
To develop and validate models for predicting 7-day neonatal readmission following vaginal or cesarean births.
Methods:
All liveborn term singleton infants without congenital anomalies in the province of Alberta who were not admitted to the NICU were identified using perinatal and hospitalization databases. A temporal split-sample was used for model development (2012-2014, vaginal n = 63,378; cesarean n = 21,225) and external validation (2014-2015, vaginal n = 21,583, cesarean n = 7,477). Multivariable logistic regression models using backward stepwise selection were used to identify predictors of 7-day readmission. We evaluated predictors of maternal age, Apgar score, length-of-stay, birthweight, gestational age, parity, residence, and sex. Hosmer-Lemeshow test and c-statistics were used to estimate calibration and discrimination.
Results:
The rate of readmission was 3.3% (95% CI 3.1%, 3.4%) and 2.1% (95% CI 1.9%, 2.3%) following vaginal and cesarean births in the development dataset. Prediction model following vaginal birth, excluding predictors of length-of-stay and birthweight, had sub-optimal performance in development (c-statistics 0.69) and validation data (c-statistics 0.68). Prediction model following cesarean birth, excluding predictors of maternal age, birthweight, and residence, had sub-optimal performance in development (c-statistics 0.62) and validation data (c-statistics 0.64). Readmission was observed in 7.9% (95% CI 7.1%, 8.8%) and 4.9% (95% CI 3.9%, 6.1%) of infants of vaginal and cesarean births, respectively, in the top quintile for the risk of 7-day readmission.
Conclusion:
Using routinely collected administrative data, we developed and validated prediction models for neonatal readmission following vaginal and cesarean births. Presently the model is sub-optimal for use in risk assessment and planning at discharge, however, additional information may improve the predictive performance.
